RESUMO
Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.
Assuntos
Biomarcadores , Encéfalo , Neuroimagem , Esquizofrenia , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/genética , Humanos , Neuroimagem/métodos , Encéfalo/diagnóstico por imagem , Encéfalo/metabolismo , Fenótipo , Imageamento por Ressonância Magnética/métodos , Aprendizado de MáquinaRESUMO
The synovium is an important component of any synovial joint and is the major target tissue of inflammatory arthritis. However, the multi-omics landscape of synovium required for functional inference is absent from large-scale resources. Here we integrate genomics with transcriptomics and chromatin accessibility features of human synovium in up to 245 arthritic patients, to characterize the landscape of genetic regulation on gene expression and the regulatory mechanisms mediating arthritic diseases predisposition. We identify 4765 independent primary and 616 secondary cis-expression quantitative trait loci (cis-eQTLs) in the synovium and find that the eQTLs with multiple independent signals have stronger effects and heritability than single independent eQTLs. Integration of genome-wide association studies (GWASs) and eQTLs identifies 84 arthritis related genes, revealing 38 novel genes which have not been reported by previous studies using eQTL data from the GTEx project or immune cells. We further develop a method called eQTac to identify variants that could affect gene expression by affecting chromatin accessibility and identify 1517 regions with potential regulatory function of chromatin accessibility. Altogether, our study provides a comprehensive synovium multi-omics resource for arthritic diseases and gains new insights into the regulation of gene expression.
Assuntos
Artrite , Estudo de Associação Genômica Ampla , Humanos , Estudo de Associação Genômica Ampla/métodos , Predisposição Genética para Doença/genética , Regulação da Expressão Gênica , Cromatina/genética , Membrana Sinovial , Artrite/genética , Polimorfismo de Nucleotídeo ÚnicoRESUMO
Human mesenchymal stem cells (hMSCs) can be differentiated into osteoblasts and adipocytes. During these processes, super enhancers (SEs) play important roles. Here, we performed comprehensive characterization of the SEs changes associated with adipogenic and osteogenic differentiation of hMSCs, and revealed that SEs changed more dramatically compared with typical enhancers. We identified a set of lineage-selective SEs, whose target genes were enriched with cell type-specific functions. Functional experiments in lineage-selective SEs demonstrated their specific roles in directed differentiation of hMSCs. We also found that some key transcription factors regulated by lineage-selective SEs could form core regulatory circuitry (CRC) to regulate each other's expression and control the hMSCs fate determination. In addition, we found that GWAS SNPs of osteoporosis and obesity were significantly enriched in osteoblasts-selective SEs or adipocytes-selective SEs, respectively. Taken together, our studies unveiled important roles of lineage-selective SEs in hMSCs differentiation into osteoblasts and adipocytes.